Rotor Time Constant Research Articles

Model Reference Adaptive Controller Based Rotor Resistance Estimation for Vector Controlled Induction Motor Drive Using Artificial Intelligence

For high performance application in industries induction motor with indirect field oriented control is used due to its excellent dynamic behavior. However, it is sensitive to changes in rotor time constant and has to be estimated online. In this paper a scheme based on the reactive power model reference adaptive controller is designed for estimating the rotor time constant. One of the major advantages of the reactive power adaptive controller is that the rotor time constant estimation is not affected due to the change in stator resistance. The estimation requires only the measurement of motor terminal voltage and current. The effectiveness of the TS fuzzy controller as an adaptive mechanism for estimation of rotor resistance during four quadrant operation of motor drive is investigated in Matlab/Simulink environment and is compared with the conventional PI and Mamdani fuzzy controller.

Flux-torque cross-coupling analysis of FOC schemes: Novel perturbation rejection characteristics

Field oriented control (FOC) is one of the most successful control schemes for electrical machines. In this article new properties of FOC schemes for induction motors (IMs) are revealed by studying the cross-coupling of the flux-torque subsystem. Through the use of frequency-based multivariable tools, it is shown that FOC has intrinsic stator currents disturbance rejection properties due to the existence of a transmission zero in the flux-torque subsystem. These properties can be exploited in order to select appropriate feedback loop configurations. One of the major drawbacks of FOC schemes is their high sensitivity to slip angular velocity perturbations. These perturbations are related to variations of the rotor time constant, which are known to be problematic for IM control. In this regard, the effect that slip angular velocity perturbations have over the newly found perturbation rejection properties is also studied. In particular, although perturbation rejection is maintained, deviations to the equilibrium point are induced; this introduces difficulties for simultaneous flux and torque control. The existence of equilibrium point issues when flux and torque are simultaneously controlled is documented for the first time in this article.

Effect of Parametric Variations and Voltage Unbalance on Adaptive Speed Estimation Schemes for Speed Sensorless Induction Motor Drives

Speed Estimation without speed sensors is a complex phenomenon and is overly dependent on the machine parameters. It is all the more significant during low speed or near zero speed operation. There are several approaches to speed estimation of an induction motor. Eventually, they can be classified into two types, namely, estimation based on the machine model and estimation based on magnetic saliency and air gap space harmonics. This paper analyses the effect of incorrect setting of parameters like the stator resistance, rotor time constant, load torque variations and also Voltage unbalance on various adaptive control based speed estimation techniques fed from the machine model. It also shows how the convergence mechanisms of the adaptation schemes are affected during these conditions. The equivalent models are built and simulated offline using MATLAB/SIMULINK blocksets and the results are analysed.

System Identification Modeling and Flight Characteristics Analysis of Miniature Coaxial Helicopter

This paper describes the identification modeling and analysis of a miniature coaxial helicopter. The first part of the paper focuses on the development of the parameterized model with an emphasis on the coaxial rotor configuration. The model explicitly accounts for the dynamics of the lower rotor and uses an implicit lumped parameter model for the upper rotor and stabilizer bar. The parameterized model was identified using frequency domain system identification. The flight data collection experiments were performed in an indoor flight-test facility built around a commercial vision-based tracking system. The second part of the paper focuses on the verification of the model's accuracy, the consistency of the identified parameters, and the analysis of the flight dynamics. The accuracy was verified by comparing model-predicted responses with flight experimental responses. The identified parameters and model's physical consistency were examined using experiments in which specific aspects of the dynamics were isolated. For example, we used video images from a high-speed camera to verify the rotor and stabilizer bar time constants. Finally, the identified derivatives were verified based on first principles to demonstrate that the derivatives are physically meaningful.

Comments on “Adaptive sliding mode observer for induction motor using two-time-scale approach”

This short communication is a discussion of the paper entitled “Adaptive sliding mode observer for induction motor using two-time-scale approach” by A. Mezouar, M.K. Fellah and S. Hadjeri published in the Electric Power Systems Research 77 (2007) pp. 604–618. In the discussed paper the authors present a current and flux sliding mode observer for the induction motor that also incorporates an adaptive law in order to estimate the inverse of the rotor time constant. However the proposed observer design uses the real value of the rotor time constant which is unknown and therefore cannot be used in the observer design.

Implementation of RBF Neural Network in Vector Control Structure of Induction Motor

The paper introduces a possible application of artificial neural networks in the control of electrical drives. For this purpose, a rotor time constant adaptation method in a vector control structure of an induction motor is chosen. The estimation of the rotor time constant is performed by a model reference adaptive system. For an adaptation algorithm, the radial basis function neural network was used. There is listed necessary mathematical description of the rotor time constant adaptation which is implemented into the vector control structure of the AC drive with the induction motor. Properties of designed algorithms with the radial basis function neural network were verified on a laboratory stand with induction motor drive. Experimental results obtained by measurements are presented and discussed.

ON LINE PARAMETER ESTIMATION OF AN INDUCTION MOTOR USING RECURSIVE LEAST SQUARES METHOD

This paper presents linear estimation techniques used to identify the stator resistance, the statorleakage inductance (transient inductance), the stator self inductance and rotor time constant of aninduction motor with measuring its speed. Such estimation is important in the determination of theachieve performance for induction motor drives. The discrete-time parameter estimation modelsexpress the relationships of the dynamic machine model in terms of measurable stator voltages,stator currents and an estimated motor speed. These models are represented by linear regressionequations from which the machine parameter vectors can be obtained using a recursive least squares(RLS) estimation algorithm. Simulation results are presented to validate the proposed estimationalgorithm with reasonable accuracy of the estimated parameters regardless of load conditions.Comparisons between experimental and calculated steady-state performances using the estimatedparameters are also presented.

DSP BASED IMPLEMENTATION OF FIELD ORIENTED CONTROL OF THREE-PHASE INDUCTION MOTOR DRIVES

The objective of this paper is to presents a practical implementation of field oriented control of three-phase induction motor based on Space Vector Pulse Width Modulation technique using Digital Signal Processing (DSP) board TMS320F2812. The control algorithm for the drive application is built with Code Composer Studio version 3.1. The motor control is divided into two control loops; inner current loop and outer speed control loop using PI controller. The rotor flux quantities are estimated using computational rotor time constant, rotor angular velocity and stator current. As a feedback of field oriented control, an incremental encoder is attached at the motor shaft and a Hall effect current sensor is used to detect the sent current to the motor. The performance of the drives system is tested under different speed command and load disturbances

Discussion on “Adaptive sliding-mode-observer for sensorless induction motor drive using two-time-scale approach”

This short communication is a discussion of the paper entitled “Adaptive sliding-mode-observer for sensorless induction motor drive using two-time-scale approach” by A. Mezouar, M.K. Fellah and S. Hadjeri published in the Simulation Modelling Practice and Theory 16 (2008) 1323–1336. In the discussed paper the authors present a current and flux sliding mode observer for the induction motor that also incorporates an adaptive laws in order to estimate the rotor speed and the inverse of the rotor time constant. However the proposed design for the observer and for the adaptive laws, employs the real value of the rotor time constant and the real value of the rotor speed, which are unknown, and therefore cannot be used in the observer design nor in the adaptive laws design.

Flux and Speed Estimation Based on the Extended State Observer for Speed Sensorless Control of Indirect Field Oriented Induction Motor Drives

A flux observer based on the extended state observer (ESO) is proposed for rotor flux estimation and speed identification of indirect field oriented induction motor drives system. The uncertain component including rotor resistance and speed in the stator current equation is extended to a new state, the ESO is then constructed. By the current estimate error, the uncertain component convergences to its actual value and the accurate rotor flux, speed and the rotor time constant are obtained. The accuracy of the ESO independent the rotor resistance and load torque variations, simulations under high and low speed show that the proposed method achieves prefect robust, and the validity and practicability is verified by simulation results.

Multi‐rate real‐time model‐based parameter estimation and state identification for induction motors

This study presents multi-rate parameter and state estimation methods for the induction motor. Based on multi-rate control theory and the extended Kalman filter (EKF) theory, a multi-rate EKF algorithm including input and output algorithms is proposed for load torque estimation in the induction motor. The methods are implemented in real-time on PC-cluster node which acts as the controller for an induction motor experimental set-up. Rotor time constant is a sensitive variable in indirect field-oriented control method. A multi-rate model reference adaptive system (MRAS) is proposed to estimate the rotor time constant in order to guarantee the high-performance control of induction motor. Experimental result verified the effectiveness of the algorithms. Simulations compare the multi-rate EKF algorithm with the traditional single-rate EKF algorithm performance to show improved performance of load torque estimator. The comparison between the traditional MRAS and the multi-rate MRAS shows the superiority of the proposed method, with a satisfactory accuracy.

Induction-Motor Rotor Temperature Estimation Using Superheterodyne Receivers

A rotor temperature estimator is proposed in this paper for grid-connected squirrel-cage induction motors during dynamic or steady-state operations. The method utilizes a pipelined architecture with two superheterodyne receivers that operate on a common complex current vector input. The first superheterodyne receiver detects motor speed by extracting an instantaneous rotor-slot-harmonic frequency from the complex current vector. The second superheterodyne receiver extracts a complex fundamental current vector from the same complex current vector. Given a few known motor parameters and a complex voltage vector, a model-reference adaptive system then produces an estimate of the rotor time constant from the superheterodyne receivers' outputs. Finally, the rotor temperature is derived from the estimated rotor time constant via a correlation between the rotor temperature and its resistance. Experimental results demonstrate that the proposed method is capable of estimating induction-motor rotor temperature on a sample-by-sample basis without using temperature or speed sensors.

Speed Sensorless Control with a Linearization by State Feedback of Induction Machine with Adaptation of the Rotor Time-constant Using Fuzzy Regulator Powered by Photovoltaic Solar Energy

In this paper, we show that the association of the PI regulators for the speed and stator currents with a control strategy using the linearization by state feedback for an induction machine without speed sensor, and with adaptation of rotor time constant powered by a solar photovoltaic energy. The solar photovoltaic energy nowadays, is one of the renewable energies sources present in various domains of applications. Moreover, the photovoltaic generator (PVG) output voltage depends of several climatic factors, such as the irradiations and the temperature. To overcome these problems, one must carries out an adequate sizing and exploits the maximum power available at the level of the (PVG). Thus the proposed structure in our work is constituted of one PV generator associated to a (DC/DC) converter controlled by using a technique of maximum power point tracker (MPPT). To adapt the rotor time constant, we proposed fuzzy tuning mechanism based on the reactive power of the machine in the permanent regime. The rotor speed is estimated by using the model reference adaptive system approach (MRAS). This method consists of using two models: The first is the reference model and the second is an adjustable one in which two components of the stator flux, obtained from the measurement of the currents and stator voltages are estimated. The estimated rotor speed is then obtained by cancelling the difference between stator-flux of the reference model and those of the adjustable one. Satisfactory results of simulation are obtained and discussed in this paper to highlight the proposed approach.

Application of RBF Network in Rotor Time Constant Adaptation

The paper presents the results of the rotor time constant adaptation method with the application of artificial neural network. Theestimation of the rotor time constant for adaptive model of MRAS is realized by the help of PI-controller and then is replaced by theRadial Basis Function network. The estimated rotor time constant is then used in the vector control of electrical drive. There werediscussed the different architectures of RBF network in the field of adaptation of rotor time constant parameter. Simulations have beenperformed in the Matlab-Simulink. Ill. 20, bibl. 8 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.113.7.606

A Novel Identification Method of Rotor Time Constant of Induction Motor

Vector control system is dependent of parameters of motor, and rotor time constant usually changes with temperature. Through analyzing the influence of rotor time constant variations on the control system performance, a novel identification method based on adaptive flux observer is presented. Different with traditional pole assignment method, it implies robust control theory and Lyapunov stability theory, by solving a linear matrix inequality (LMI) to obtain the feedback gain matrix. The simulation results show that this method can identify the rotor time constant of induction motor accurately, and it has rapid converge, good indiscrimination degree and strong robustness.

Parameter Identification of an Induction Motor Drive with Magnetic Saturation for Electric Vehicle

This paper presents a simulation model and a parameter identification scheme of an induction motor drive for electric vehicle. The induction motor in automotive applications should operate in very high efficiency and achieve the maximum-torque-per-ampere (MTPA) feature even with saturated magnetic flux under very high torque. The indirect vector control which is typically adopted in traction drive system requires precise information of motor parameters, particularly rotor time constants. This work models an induction motor considering magnetic saturation and proposes an empirical identification method using the current controller in the synchronous reference frame. The proposed method is applied to a 22kW-rated induction motor for electric vehicle.

A Luenberger-sliding mode observer with rotor time constant parameter estimation in induction motor drives

The performance and efficiency of an induction motor drive system can be enhanced by online estimation of critical parameters such as rotor time constant. A novel Luenberger-sliding mode observer with a parameter adaptation algorithm is proposed in this paper to compensate for the parameter variation effects. The observer is comparably simple and robust relative to the previously developed observers, and yet suitable for online implementation. Simulation studies for the proposed method were conducted in a MATLAB environment. Observer constants and the control parameters were tuned during the simulation studies and used during the experimental study stage. Experimental verification of the developed algorithm was performed with an induction motor using the rotor flux-oriented vector control. The comparative results and related overall conclusions are presented accordingly.

H ∞ design of rotor flux-oriented current-controlled induction motor drives: speed control, noise attenuation and stability robustness

This study deals with the design of H∞ controllers for speed control of rotor flux-oriented current-controlled induction motors. The mixed sensitivity problem (robust stability and performance) is initially revisited, and is shown, based on practical experiments, that when the rotor time constant is the uncertain parameter, it is necessary to deploy conflicting weighting functions, therefore invaliding its application in the design of current-fed induction motors. Two other H∞ problems are addressed: (i) a one-block problem for speed control with tracking and transient performance objectives; and (ii) a two-block problem for speed control with tracking/transient performance and noise attenuation objectives. An important part of H∞ design is the model of the system to be controlled. In this study, the system composed of the inverter, estimator and induction motor will be modelled as a first-order system, and experiments for the identification of the gain and the time constant are proposed. It is also suggested how to properly correct an initial estimation of the rotor time constant in order to make the actual plant (inverter-induction motor) behave as a first-order linear system. The model accuracy and the efficiency of the H∞ controllers are validated by experiments carried out in a real system.

Adaptive Nonlinear Direct Torque Control of Sensorless IM Drives With Efficiency Optimization

Efficiency optimization of induction motor (IM) drives is a major subject based on these drives' extensive use in the industry. Among the different proposed methods, a model-based approach (MBA) seems to be the fast one. However, this method needs the motor parameters that must be correctly identified. On the other hand, a search-based approach (SBA) is a parameter-independent method but needs a greater convergence time. In this paper, a novel model-based loss-minimization approach is presented, which is combined with a backstepping direct torque control of the IM drive. An improved search-based method for efficiency optimization is also introduced. The proposed controller is realized in the stationary reference frame and has a fast-tracking capability of rotor flux and electromagnetic torque. Moreover, a sliding-mode rotor-flux observer is introduced, which is employed for simultaneous determination of rotor-flux space vector, rotor speed, and rotor time constant. The proposed control idea is experimentally implemented in real time using a field-programmable gate-array board synchronized with a personal computer. Simulation and experimental results are finally presented to verify the effectiveness of the method proposed.

Speed-sensorless control of induction motor based on reactive power with rotor time constant identification

This study presents a modified model reference adaptive system speed estimator for induction motors (IMs) based on regulation of the instantaneous rotor magnetising reactive power, which does not use integration or stator resistance in the reference model. The proposed modifications allow analytical tuning and facilitate implementation of the estimator in a digital signal processor. The detuning of the estimator with respect to the rotor time constant is exploited as a source of information in a novel parallel identification mechanism for this parameter. The rotor time constant error is obtained by correlation of the high-frequency components of the speed estimator error and the torque producing current, thus enabling simultaneous estimation of the IM speed and the rotor time constant. The robustness and accuracy of the proposed schemes are verified experimentally.